Time has always been the new currency Changemakers, the pioneers of change, face enormous challenges today: the world demands that they not only think multidimensionally, but also act quickly. Whether in the area of circular economy, social innovations or managing sustainable companies - the ability to make informed decisions based on comprehensive information is a key skill. However, the flood of information is increasing exponentially. Reports, studies and data are piling up, while the time available is stagnating or even decreasing. This is where the "Executive Summary Agent" comes in. This AI tool drastically reduces the time required to process complex information without compromising on quality. For changemakers, who often have to balance between strategy and operational implementation, this means more time for the essentials and a much more precise basis for decisions. Artificial intelligence as a tool for change? Changemakers are not just decision-makers, they are pioneers. Their work requires both quick results and a careful examination of complex issues. Access to high-quality information is essential - and this is where the problem arises: reading and analyzing extensive studies and reports and gaining actionable insights from them is a time-consuming process. One of my clients, Basel Circular , an initiative to promote the circular economy in Basel SMEs, is an example of exactly this challenge. Their managers must continuously evaluate new reports and scientific papers in order to gain relevant insights for practice, for new services and offers. But how can they do this efficiently without overlooking essential details - or even neglecting their other management functions? An astonishingly simple solution: The “Executive Summary Agent” For me, the solution was to build a customized agent that could process, analyze and curate information based on my expertise. For me, the AI tool developed for Basel Circular is a prime example of how technology and human innovative spirit - or human pragmatism, depending on the case - can come together to solve a real (customer) challenge and create real, tangible benefits. Methodically, I integrated the following principles into the AI agent: Structured processes: The “Executive Summary Agent” works with a clear sequence of work steps. The “Chain of Thought” method ensures that even complex tasks are broken down into digestible steps. Defined roles: The AI takes on predefined roles such as “research assistant” or “critical professor” in order to make the results as accurate and understandable as possible. I could also say that it successfully emulates the complexity of human decision-making systems. Iterative quality: After the first draft, the results are automatically checked in different roles and iteratively revised in order to significantly increase the quality again. This is nothing other than the Pareto rule. The goal is to achieve 80% result (quality) with 20% effort (time input). This is only possible if the AI agent has a built-in iteration level. A practical example: Basel Circular Basel Circular now regularly uses the Executive Summary Agent to save valuable time and resources. The ability to summarize scientific studies more quickly and precisely leaves significantly more room for strategic thinking and operational decisions. A concrete scenario: A 180-page study that would have originally taken 360 minutes to read is summarized in less than a minute by the "Executive Summary Agent". Not only are the essential content extracted, but findings are also critically reflected upon and recommendations for action derived. The AI agent enables information processing to be accelerated by a factor of x360 - a real game changer for changemakers. Broader areas of application? The benefits of the “Executive Summary Agent” naturally extend far beyond the circular economy. Whether in areas such as strategic planning, sustainable innovation or social transformation – the tool fundamentally enables a way of working that is not only faster but also more precise. Checklist: How changemakers integrate the tool into their everyday lives Step 1: Identify the most important reports or studies that need to be analyzed regularly. Step 2: Define the relevant roles and work steps that the AI should perform for your specific requirements. Step 3: Use the insights gained to improve your strategic decisions and communicate your vision more clearly. Technology as a partner in change: AI tools for changemakers For changemakers, the use of technologies such as the "Executive Summary Agent" is not a gimmick, but a necessity. It makes it possible to handle the flood of information without compromising on quality. The work is not automated, but rather supplemented. Conclusion: The tool creates space for what really matters: strategic considerations, creative problem solving and the design of a better future. In a world that is becoming ever faster, time is the most valuable resource - and the ability to use it sensibly is a decisive competitive advantage. If you are interested in using similar AI tools for changemakers in your own information processes and need support (no strings attached) to do it right – please get in touch. Thank you for reading ❤️ Stay alert and critical, don't lose your sense of humor and be sure to forge alliances with other conscious changemakers! Your Patrick Castellani, info@patrick-castellani.com Bonus round: Professor Tüpfli

In a world full of complexity, we are constantly faced with the challenge of evaluating information and making the right decisions. Reports, studies and data streams challenge us - not only in terms of content, but also at the level of our values. It is clear to me that it is not enough to be faster or to work more efficiently. As leaders, our goal is to bring clarity to decisions and to take responsibility. But how can we achieve this in a world that is becoming increasingly complex? Technologies like AI can play a key role in this. They are tools that help us understand better, analyze more clearly and act more consciously - if we use them with the right attitude. But tools alone are not enough. This is where the Conscious Changemaker comes in: someone who uses technology in a targeted manner to cut through the flood of data and challenges without losing human responsibility. It is an approach that creates clarity, makes complexity navigable and makes decisions in a values-oriented context. How AI makes complexity 'comprehensible' I work with complex documents every day: studies, reports and analyses that often run to hundreds of pages. The biggest challenge? Finding out which information is really relevant - and which only pretends to be relevant or distracts us from the essential thing - namely, gaining clarity in decisions. This is exactly where I specifically use AI. It analyses the structure for me, evaluates the data quality and highlights potential weaknesses. This means: Clarity: I can see immediately whether a study or report is even relevant. Time saving: Instead of reading for hours, I get a precise analysis in minutes. Responsibility: I can concentrate on the really important decisions. This does not mean that AI decides for me. It supports me in asking the right questions and finding well-founded answers - an indispensable tool for anyone who wants to deal with complexity more consciously. Of course, the use of AI also has its limits. It is not a substitute for our judgment and is not a panacea. Every technology is only as good as the intention with which it is used. Awareness and responsibility remain the key factors. If you want to learn how I use AI to advance the cause of changemakers and support leaders, watch this video: Use Case AI | 800% acceleration of research processes through AI (Video 1) 👩💻 Three lessons I learned from using AI Less is more: Not every piece of information is crucial. AI helps me to grasp the core of a document - the statements that really count. Everything else is deliberately kept blurred so as not to distract from the central points. This "blurring" describes the conscious decision not to over-analyze information on the fringes of a topic, as it often distracts more than it contributes to the quality of the decision. This reduction creates space for more precise and effective decisions. Questions are more important than answers: The quality of an analysis depends on the questions I ask. AI does not provide definitive truths, but rather condensed summaries with a high degree of probability. This means that I formulate clear questions to bring out the crucial points, while accepting that not all answers are perfect in every detail. It's about creating clarity at the core without getting lost in unimportant details. Awareness beats speed: Saving time is an advantage, but not the goal. AI helps me to understand complexity more quickly, but the responsibility for my decisions remains with me. It's about consciously using the information that AI provides, accepting its imprecision and using it to enhance my judgment. These lessons have changed the way I deal with complexity. They have not only made me more efficient, but have also taught me to differentiate between the core of a decision and the peripheral aspects. It's not about perfection, but about using tools that create core conciseness and enable conscious decisions - with clarity about what counts in the long term. Clarity in Decisions: Why AI is just the beginning Technologies such as AI can help to filter out the key messages from the flood of information - precisely and efficiently. But they are only a tool that helps us create clarity. The real responsibility lies with us: to make decisions consciously and preserve the context in which they stand. As a conscious changemaker, this means not simply viewing technology as a solution, but actively integrating it into the way we work. It's about asking the right questions and critically evaluating the answers without outsourcing the quality of decisions to technology. Transformation happens when we use technology to make complexity manageable, while keeping our values and responsibilities in mind. In this way, a data-driven analysis becomes a conscious, value-oriented process that enables us to act in a complex world. From Processes to Principles This is what distinguishes the new way of working of the Conscious Changemaker: Instead of seeing documents as a burden, they become an opportunity to ask the right questions. We use reports and data not just to find quick answers, but to understand what really matters. Every document becomes a starting point for deeper insights and better decisions. Instead of control, we focus on clarity - not through speed, but through conscious work. It's not about always being faster. Conscious working methods mean investing time in the things that count and focusing on what creates long-term value - for ourselves and our environment. Instead of being put off by complexity, we see it as a space in which new things can emerge. Complex problems are not obstacles, but opportunities to create new connections, broaden perspectives and promote innovation. Quo Vadis? Working as a conscious changemaker is not an easy path. Nor is it a path that you always walk with the certainty of doing everything right. It is a path full of questions, doubts and occasional setbacks. But it is a path that is worth taking - especially if you are not walking it alone. For me, two things are essential: First, to stay awake - because nothing is more dangerous than habits and assumptions that we no longer question. Second, not to lose our sense of humor. Because if we learn to laugh at ourselves and the absurdity of some situations, we not only retain the energy to carry on, we also retain the humility needed to integrate the many different perspectives that this world allows into a more meaningful overall picture. And most importantly: we need alliances. Exchange with others who think alike, share similar values and are ready to step out of the autodrive module, take on responsibility and create something new together. No one can change the world alone - but together we can do more than we often think we can. Perhaps that is precisely where the biggest difference lies: the path of a conscious changemaker is not that of a lone fighter, but that of an ally. Critical, alert and with a wink towards the future. Your Patrick Castellani, info@patrick-castellani.com

Definition The Sustainable Finance Disclosure Regulation (SFDR)  is a European Union regulation introduced in 2019 as part of the EU Action Plan for Sustainable Finance. Its primary goal is to increase transparency in financial products regarding Environmental, Social, and Governance (ESG) factors, allowing investors to make informed decisions. The SFDR combats greenwashing and ensures that sustainable investments are measurable and comparable. The SFDR categorizes financial products into three main categories: Article 6:  Products without specific sustainability objectives. Article 8 ("light green"):  Products promoting environmental or social characteristics. Article 9 ("dark green"):  Products targeting specific sustainable investment objectives. In the broader context of sustainable business solutions, circular economy, and social impact , SFDR is a foundational tool for steering financial flows toward sustainable business models and fostering long-term ESG-driven transformations. Why SFDR is Important for Changemakers Patrick Castellani:"SFDR is more than just a regulation. It’s an opportunity to redefine values and shift the focus from mere profit maximization to meaningful impact. Unlike the classic McKinsey-style ‘more revenue, more market share’ mindset, SFDR encourages a holistic perspective. For changemakers, this means investing not only in profits but in measurable benefits for society and the environment. Why does this matter? Because companies can no longer thrive on numbers alone. Customers, employees, and partners increasingly demand accountability. SFDR provides the tools to build transparency and trust. For Swiss SMEs especially, adhering to SFDR principles can enhance competitiveness and position them as leaders in sustainable innovation." Mental Shortcut Think of SFDR as a certificate for transparency . Imagine buying organic vegetables. You want to ensure they’re genuinely organic—so you rely on clear labels and standards. SFDR acts as this “label” for sustainable investments, ensuring you know whether a fund is truly green or just pretending to be. Another way to see it: SFDR is like a GPS for sustainability . It guides companies and investors on the path to their destination—a more sustainable economy. Without clear guidelines, they risk veering off course, ending up with greenwashing or inefficient projects instead. Application of Sustainable Finance Disclosure Regulation (SFDR) SFDR is actively used across various sectors: Banks and Asset Managers:  They classify products under Articles 8 and 9 to attract ESG-conscious investors. SMEs and Companies:  SFDR helps improve sustainability practices and gain access to sustainable financing. Investors:  They use SFDR as a roadmap to identify projects with measurable social and environmental impact. For example, the Zürcher Kantonalbank (ZKB)  uses SFDR to clearly label its sustainable funds. Similarly, Amundi  and BlackRock  have integrated SFDR-compliant measures to strengthen their ESG market positions. Real World Examples Switzerland: Zürcher Kantonalbank (ZKB) – ESG Investment Strategy Aligned with SFDR The Zürcher Kantonalbank (ZKB), one of the largest banks in Switzerland, adapted its ESG investment strategy to SFDR requirements to enhance transparency in sustainable financial products. Implementation: ZKB categorized its funds according to SFDR Articles 8 and 9 and published detailed reports on ESG factors such as CO₂ emissions and social projects. Impact: Increased transparency for investors. Promotion of sustainable investment strategies among Swiss investors. Positioned ZKB as a leading provider of sustainable financial products. Source: ZKB ESG Strategy Report Europe: Amundi Asset Management – Article 8 and Article 9 Products Amundi, Europe’s largest asset manager, implemented extensive measures to classify all funds under SFDR. Implementation: Article 8 products (“light green”):  Funds promoting environmental or social characteristics. Article 9 products (“dark green”):  Investments explicitly pursuing sustainable goals. Introduction of an ESG rating system integrated into fund evaluations. Impact: Strengthened position in the ESG market, with significant growth in sustainable funds. SFDR classifications helped reduce greenwashing. Source: Amundi SFDR Statement Global: BlackRock – Integration of SFDR in Global Investment Strategies BlackRock, the world’s largest asset manager, leveraged SFDR to promote sustainable investments and ensure transparency in the ESG space. Implementation: Applied SFDR classifications to its European funds and disclosed material sustainability risks. Integrated climate risks into its investment strategy based on SFDR guidelines. Impact: Increased transparency and investor trust. Promoted projects with positive social and environmental effects. Source: BlackRock Sustainability Strategy Benefits The Benefits of SFDR for {Audience}, Including Practical Examples The SFDR offers numerous advantages for {audience}, such as executives, changemakers, and SMEs, by promoting sustainable business practices and investment decisions: Transparency: SFDR compels companies and funds to disclose detailed ESG data, enabling {audience} to make well-informed decisions. Building Trust: By reducing greenwashing, SFDR strengthens stakeholder confidence in the sustainability of products and projects. Market Access: Organizations offering SFDR-compliant products or projects have a greater chance of being included in ESG funds. Practical Example 1: UBS Asset Management certified numerous funds under SFDR Articles 8 and 9, leading to a doubling of interest from ESG investors. Practical Example 2: Nestlé reports on sustainability risks in line with SFDR, attracting new impact investors as a result. Challenges Challenges and Obstacles in Applying SFDR While SFDR represents a significant step toward sustainability, its implementation comes with several challenges: Regulatory Complexity: Many companies, particularly SMEs, struggle to understand and accurately implement the technical details and reporting requirements of SFDR. Data Availability: The regulation demands extensive ESG data, which smaller organizations often find difficult to obtain. Costs: Implementing SFDR guidelines involves high expenses, such as for ESG analyses, software, and consultants. Lack of Harmonization: The interpretation of SFDR requirements is inconsistent, leading to uncertainties and varied applications. Practical Example: A medium-sized company in Switzerland reported challenges in collecting sustainability metrics for its supply chains under SFDR, as data from third-party providers was incomplete. What Not to Do How SFDR Should NOT Be Used, Including Practical Examples There are several pitfalls in the implementation of SFDR that companies must avoid: Greenwashing: Companies should not use SFDR to make sustainability claims they cannot fulfill. This can lead to reputational damage and legal consequences. Incomplete Data: Providing insufficient or inaccurate data undermines the credibility of reports and can deter investors. Lack of Strategic Integration: SFDR should not be treated as merely a reporting obligation but rather as an opportunity to embed sustainability into the company’s strategy. Practical Example: A European asset manager faced criticism for declaring funds as Article 8 products, despite them not meeting all SFDR criteria. This resulted in a massive withdrawal of investors. How to Start Step 1:  Conduct an internal ESG assessment. Step 2:  Invest in tools like Sustainalytics or MSCI ESG Manager. Step 3:  Provide regular training on SFDR requirements. Step 4:  Partner with specialized ESG reporting consultants. Framework & Tools Practical Tips and Frameworks for Successfully Implementing SFDR Prioritize Data Management: Companies should implement systems to collect and analyze ESG data to meet reporting obligations. Tools such as MSCI ESG Manager or Sustainalytics can assist in this process. Training and Education: Employees should be trained in SFDR compliance, particularly in areas like data analysis and reporting. Leverage Partnerships: Collaborating with specialized consultants or ESG rating agencies can simplify implementation. Regular Review: Companies should regularly review and update their SFDR data to ensure ongoing compliance. Frameworks: Task Force on Climate-Related Financial Disclosures (TCFD):  Supports companies in integrating climate risks into their reporting. UN Principles for Responsible Investment (PRI):  Provides guidelines for incorporating ESG factors. Sources: https://www.fsb-tcfd.org https://www.fsb-tcfd.org Sustainalytics ESG Solutions Wordcloud SFDR, ESG, Greenwashing, sustainable finance, Article 8, Article 9, EU Green Deal, transparency, SMEs, changemakers, circular economy, social impact, sustainability, climate risks Studies & Papers Here are five recent, in-depth studies and publications on the SFDR (Sustainable Finance Disclosure Regulation) that provide key insights into the regulation's impacts, challenges, and benefits: Sustainable Finance and the SFDR: Enhancing Transparency in ESG InvestmentsAuthor(s):  European Securities and Markets Authority (ESMA) Summary: This study examines the SFDR's impact on transparency in the financial sector. It highlights how the regulation influences access to ESG investments and the challenges financial actors face in implementing Articles 8 and 9. Key Findings: SFDR significantly reduces greenwashing. Data availability disparities between large and small companies. Publication Year:  2022 Link:  [ESMA Report on SFDR] The Role of SFDR in Achieving the EU Green Deal ObjectivesAuthor(s):  European Commission Policy Papers Summary: This publication analyzes how the SFDR supports the EU Green Deal goals, particularly by fostering sustainable investments. It highlights how companies and financial service providers can integrate long-term climate objectives. Key Findings: SFDR acts as a catalyst for economic and financial transformation. Importance of standardized ESG metrics Publication Year:  2021 Link:  [EU Commission Green Deal and SFDR] Assessing the Effectiveness of SFDR in Addressing Greenwashing RisksAuthor(s):  Deloitte Insights Summary: This study evaluates the effectiveness of the SFDR in minimizing greenwashing. It presents case studies demonstrating how unclear ESG data continues to pose risks for investors. Key Findings: Opportunities for improvement in data collection. Recommendations to strengthen SFDR regulations. Publication Year:  2023 Link:  [Deloitte Insights: SFDR] SFDR and Its Impact on Small and Medium Enterprises (SMEs)Author(s):  PwC Research Group Summary: This publication focuses on the challenges and opportunities for SMEs in implementing the SFDR. It explains how smaller companies can leverage disclosure requirements to improve their competitive position. Key Findings: High costs associated with data provision. SMEs benefit from better access to ESG investors. Publication Year:  2022 Link:  [PwC Report on SFDR and SMEs] Measuring the Alignment of SFDR with the UN SDGsAuthor(s):  United Nations Environment Programme Finance Initiative (UNEP FI) Summary: This study explores how the SFDR contributes to achieving the UN Sustainable Development Goals (SDGs). It analyzes overlaps between SFDR indicators and SDG targets such as climate action and social justice. Key Findings: SFDR serves as a bridge between financial regulation and global sustainability. Need for globally harmonized disclosure standards. Publication Year:  2023 Link:  [UNEP FI: SFDR and SDGs]

Definition of IFRS S1 and S2 Sustainability Reporting: The International Sustainability Standards Board (ISSB) has introduced IFRS S1 and IFRS S2 as groundbreaking tools for sustainability reporting. These standards aim to bring coherence and transparency to how organizations disclose their sustainability-related financial information. IFRS S1  sets out the general requirements for sustainability disclosures, while IFRS S2  focuses specifically on climate-related risks and opportunities. Together, they offer a unified framework for aligning corporate strategy with environmental, social, and governance (ESG) goals. Why ‘IFRS S1 and S2’ Matter for Changemakers: In today’s fast-changing landscape, sustainability has moved from a peripheral concern to a strategic priority. Leaders and organizations are now expected to demonstrate responsibility, resilience, and foresight. IFRS S1 and S2 provide the structure to achieve this, making sustainability reporting a tool for trust-building and long-term value creation. IFRS S1 and S2 allow businesses to integrate sustainability deeply into their operations, fostering transparency and aligning with global goals like the Paris Agreement. For changemakers, these standards are essential for ensuring that economic growth is coupled with social and environmental stewardship. Mental Shortcut: Think of IFRS S1 and S2 as a compass guiding businesses toward sustainable success. They help organizations navigate the complexities of ESG reporting, much like a compass ensures you stay on course even in uncharted territory. Applications in Business: Strategic Alignment: Companies can integrate sustainability risks and opportunities into their overall strategy, ensuring resilience in the face of climate and market changes. Investor Communication: By providing standardized ESG disclosures, IFRS S1 and S2 help businesses meet the expectations of investors seeking transparent and comparable data. Operational Integration: These standards encourage organizations to refine their data collection, streamline processes, and align operations with sustainability objectives. Regulatory Compliance: As ESG reporting becomes mandatory in many regions, IFRS S1 and S2 offer a framework to meet these growing requirements effectively. Real-World Examples: Swiss Re (Switzerland): As a leader in the reinsurance sector, Swiss Re has aligned its climate disclosures with the recommendations of the Task Force on Climate-related Financial Disclosures (TCFD). These efforts mirror the principles of IFRS S2, showcasing Swiss Re’s commitment to sustainability and transparency. More information here . Triodos Bank (Europe): The Dutch-based Triodos Bank integrates sustainability into its core operations and reporting. Using frameworks akin to IFRS S1 and S2, Triodos ensures its financial products align with ESG goals while maintaining transparency for stakeholders. More information here . Patagonia (Global): Known for its dedication to environmental advocacy, Patagonia employs reporting practices that reflect the spirit of IFRS S1 and S2. This reinforces its commitment to systemic impact and environmental stewardship. More information here . Benefits for SMEs and Purpose-Driven Organizations: Enhanced Transparency: Standardized ESG disclosures build trust with stakeholders and investors. Competitive Advantage: Businesses that prioritize sustainability can distinguish themselves in an increasingly ESG-conscious market. Long-Term Resilience: Accounting for sustainability risks ensures organizations are better prepared to navigate uncertainties. Market Access: Aligning with global reporting standards can attract international investors and partners. Challenges and Solutions: Challenges: Resource Intensity:  Smaller organizations may struggle to allocate resources for implementing these standards. Data Complexity:  Gathering and analyzing ESG data across various operations requires robust systems. Cultural Resistance:  Integrating sustainability into corporate DNA may face internal pushback. Solutions: Begin with a gap analysis  to assess current reporting against IFRS requirements. Invest in training programs  to enhance employee understanding of sustainability principles. Utilize external consultants  to guide the implementation process and identify cost-effective solutions. What Not to Do: Avoid greenwashing —misrepresenting sustainability efforts can lead to reputational damage and legal consequences. Instead, focus on genuine, measurable actions that align with IFRS S1 and S2 requirements. How to Start: Conduct a Gap Analysis: Compare existing reporting practices with IFRS standards to identify areas for improvement. Create a Phased Plan: Gradually implement IFRS S1 and S2 to minimize disruption. Engage Stakeholders: Communicate with employees, investors, and partners to build alignment and support for sustainability goals. Frameworks & Tools: Task Force on Climate-Related Financial Disclosures (TCFD): Complementary guidelines for climate-related reporting. Global Reporting Initiative (GRI): Established standards for sustainability reporting. SASB Standards: Industry-specific metrics for ESG reporting. ESG Software Tools: Platforms like SpheraCloud and Workiva facilitate efficient data collection and reporting. Wordcloud: IFRS, ESG, climate risks, transparency, sustainability reporting, systemic impact, financial resilience, stakeholder trust, governance, operational alignment. Studies & Papers: KPMG.  "ISSB veröffentlicht IFRS S1 und S2." KPMG Deutschland, 26. Juni 2023. Verfügbar unter: KPMG BDO.  "ISSB veröffentlicht IFRS S1 und IFRS S2." BDO Deutschland, 26. Juni 2023. Verfügbar unter: BDO Baker Tilly.  "Auswirkungen von IFRS S1 und IFRS S2 auf die zukünftige Nachhaltigkeitsberichterstattung." Baker Tilly Deutschland, 26. Juni 2023. Verfügbar unter: Baker Tilly IFRS Foundation.  "ISSB issues inaugural global sustainability disclosure standards." IFRS, 26. Juni 2023. Verfügbar unter: IFRS EY.  "ISSB issues inaugural IFRS sustainability disclosure standards." Ernst & Young Global Limited, 26. Juni 2023. Verfügbar unter: EY Assets

The full article will appear in the fall of 2021 in a publication by Carl Auer Verlag on the topic of "Meaningful Organization - Pros & Cons".. In the past, there were the chants. And before that - long before that - already the dances. With voice, foot and beating heart we told each other the star run. The empty moon and the perfect one. And under the moving sky fire our life and death in the change of the seasons. This too was a dance and it was only right to stamp it too into the clay of this world, to breathe it and to give sound to breathing. This is how we created the world from ourselves. Gave it meaning. Gave it to each other. Sang ourselves into the fabric of life. [Rabbit Hole 20] Something about dancing bees and the meaning of storytelling I remember my grandfather and an incident that I have long tried to grasp in all its significance. By remembering, I tell. By telling, I create myself. The incident occurred on a warm May day in 1977. Jimmy Carter was President of the United States at the time, the world was still peacefully dozing in the Cold War, and I was a curious six-year-old setting out to discover the adult world. I remember. Of my grandfather rushing excitedly across the meadow in front of the farmhouse around noon. To the other end of the property, where it adjoined the old railroad shed of the local streetcar. [Rabbit Hole 21] A brief dwell on systemic honey pots When people ask me whether an organization should and may be meaningful - and I am indeed asked about this again and again in my work as an organizational consultant - I find it difficult to give a clear answer. I then think of my grandfather and his bees, on which he wanted to impose more than was familiar to their nature. Above all, he wanted them to dance to his own tune. I think that could only go wrong. In his hive - and if you'll allow me the metaphorical translation - in human organizations, too, of course. Where people come together and organize themselves toward a common goal, the formation of meaning cannot be avoided at all. In a sense, it is inherent in the system. Organizations are always also meaning machines in which people plan, shape, and evaluate their relationships with other people in the context of expectation structures. They do this, of course, by communicating with each other. On the somewhat overrated rational factual level and even more on the relational and often unconscious meaning level. The latter is the home of experiences, emotions, values, unquestioned basic assumptions - e.g. prosperity is proportional to growth - and in general our heuristics in dealing with the phenomena of this world. Something else characterizes this level: the information is not structured logically, but narratively. Just like the complex micro and macro models for a successful life that are ultimately constituted out of them. We do not experience world directly, we narrate it to ourselves. And every narrative is a construction of meaning of the world. In short: meaning is made. It does not simply exist, but is narratively constructed in interaction with other people. Therefore, it is not whether meaning is made that is interesting to me, but how. For example, how much co-design potential is granted to the participants in such meaning-making processes and how dynamically the meaning-making can update itself, because what makes sense today can be complete nonsense tomorrow. [Rabbit Hole 22] How to Reconstruct Meaning and Identity

Interview with Bonum, November 2020 How can foundations use storytelling and narrative methods to become visible and tell their future in a meaningful way? In this interview, Patrick Kappeler, founding member of the Storyteller Academy, explains how it works. Patrick Kappeler, what do you mean by storytelling In principle, storytelling means nothing more than packaging bare figures and data in such a way that people understand them immediately. Stories fire an incredible number of brain regions at the same time and therefore remain in our memory for a long time. And stories are immediately understood by our subconscious, the part of our brain that makes 95 percent of all decisions every day. Why is it important to tell the future To put it somewhat exaggeratedly: If you don't tell your own future, you don't have one. After all, a future narrative is nothing more than a bet on the future. If you don't have a convincing story to offer, people will turn away from you. Meaningful stories, so-called narratives, are such bets on the future. They organize how communities feel, think, and act toward a common goal. Powerful stories touch and transform people. That's how to use storytelling for social impact. Don't numbers, facts, and figures do the same? No. Look at the climate debate. We all know the troubling projections. Yet, for all our reason and logic, we don't seem to be able to counteract it in time. Brain research has shown: Man is not a thinking machine that feels, but a feeling machine that thinks. It is not the mind that we have to convince, but the feeling. This is exactly what narratives do. They flirt uninhibitedly with our logic of affect and win us over to even the most difficult tasks and toils. "Man is not a thinking machine that feels, but a feeling machine that thinks." Many bets on the future look rather bleak at the moment. True. Large order structures and ladder narratives, including the economic growth narrative, are eroding and losing their meaning-making power for many. We are moving into a vacuum. New visions for successful coexistence are only just emerging. Here I see an opportunity for foundations to become even more involved in the social discourse. It will be crucial to get others to join in the conversation. Why is that important? An attractive vision is of no use if no one wants to share it. Only when employees and customers participate in the storytelling process can organizations tap their full potential. Then forces are released that can achieve great things. Then miracles happen. And what does storytelling bring? Visibility, engagement, movement. Storytelling is a technique for structuring information and experiences in such a way that our brains understand them crystal clear, even at the emotional level. Let me give you an example: If you claim on your website to promote sustainability, you remain in a meaningless abstraction. It would be wiser to tell the story of Eve, the young wine farmer, about this value: Eve, with your help and against her parents' opposition, converted production completely to organic and now sells one of the best wines in the region. It is the concrete narrative that makes the abstract understandable, relevant and exciting. Storytelling is a fundamental prerequisite for remaining visible in an increasingly complex world, for building trust, for more successful fundraising, and for telling the future in a meaningful way together with others. What might a meaningful future narrative look like and how to use storytelling for social impact? I observe that more and more people long for a tender economy of togetherness, connection, responsibility, and meaningful aliveness. These needs are powerful sources from which we draw inspiring future narratives for ourselves and the community and pass them on to others with heart and mind. Curious about how you can harness the power of storytelling for your business? I look forward to connecting. Contact: p.castellani@imotions.ch

What generative language AIs can do is astonishing – although their abilities strongly remind me of a talking parrot, which also doesn't really know what it’s repeating. Despite apparent linguistic competence, the parrot never grasps the multifaceted meaning of human language and experience. For many simple applications, such as marketing tasks, the statistical mimicry abilities of the AI parrot are entirely sufficient. However, when the tasks and thus the requirements for generative language AIs become more complex, it’s a different story. As far as I know, without real language understanding and genuine reasoning ability, no complex tasks can be handled. This applies to both humans and AIs. In the hope of somehow compensating for these deficiencies, AI researchers and engineers around the world are now engaged in a frenzied "winner-takes-all" race to develop increasingly larger and more sophisticated AI language models. ...without real language understanding and genuine reasoning ability, no complex tasks can be handled! What Nature Teaches Us About Intelligent Design Whether the size of the model and fine-tuning will remedy the reasoning deficit of current language models (LLM, Large Language Model) remains questionable. I seriously doubt this strategy. Not because I am a PhD AI expert, but because I only need to look around to get an immediate sense of how nature builds powerful systems. Instead of having one large, cumbersome system, it generally uses many small units that work together to solve complex tasks.Think of a single cell in your body, which can only perform small tasks such as absorbing nutrients or regulating pH levels. However, when this cell collaborates with many other cells and becomes part of an organ like the liver, this organ can handle much more complicated tasks, such as detoxifying the body or storing energy.  This illustrates the principle of emergence: when many simple units work together, new capabilities and properties suddenly arise that the individual units alone do not possess.  Cognition also organizes and scales in this way (Michael Levin, 2019, Scale-Free Cognition). Another characteristic of such natural systems is that they are not only powerful but also extremely energy- and resource-efficient – both in construction and operation! If they were not, evolution would quickly eliminate them. Admittedly, AI research has already learned much from nature. Artificial neural networks, for example, were what led to the technological breakthrough and enabled the astonishing capabilities of current LLMs. However, instead of building ever-larger LLMs – which is akin to inflating a single cell to the size of an organ – I recommend a more elegant strategy: the bundling of small cognitive subsystems, which we call agents, into increasingly larger and more powerful cognitive systems, known as Multi-Agent Systems (MAS). I would like to examine three critical aspects for functional Multi-Agent Systems in more detail: The configuration/architecture of an MAS The organization of knowledge/expertise in an MAS The organization of communication in an MAS Small but Mighty: Multi-Agent Systems As the name suggests, a Multi-Agent System consists of various agents with different tasks, knowledge, and tools that can work together to handle complex tasks.For example, imagine an MAS that helps me with English vocabulary in the context of business negotiations. One agent conducts the conversation, another analyzes my progress, a third gives recommendations, another compares my responses with an expert database, and perhaps another oversees and orchestrates the entire process. In short, in an MAS, a whole team of experts works together invisibly to find the best solution for me. Anyone who has worked with advanced prompt engineering knows how difficult it would be to solve this task with a single prompt, in technical jargon known as 'one-shot.' The advantages of a Multi-Agent System (MAS) over a Single-Agent System are clear: Reduction of Complexity and Specialization:  The work is divided into smaller, specialized tasks, which reduces the complexity of the system. Increased Solution Intelligence and Emergence Effects:  New, intelligent solutions arise through the collaboration of multiple agents. Reliability and Precision:  Multiple agents can perform the same task, which increases reliability and accuracy. Scalability and Expandability:  MAS can be easily expanded by adding new agents without changing the entire system. Flexibility and Adaptability:  MAS can flexibly respond to changing requirements or environments, as agents work independently and adapt. Fault Tolerance and Redundancy:  By distributing tasks among multiple agents, the system can better handle errors. If one agent fails, others take over its tasks. Parallel Processing and Speed:  MAS can process tasks in parallel, which increases processing speed. Specialization and Expertise:  Each agent can be specialized in a specific task, which improves the efficiency and quality of processes. Autonomy and Decision-Making:  Agents can autonomously make decisions and perform actions, reducing the need for constant human supervision. Interdisciplinarity and Knowledge Transfer:  MAS enable the integration of knowledge and skills from various disciplines, leading to more comprehensive and well-founded solutions. The "Right" Architecture for Multi-Agent Systems The architecture of a Multi-Agent System depends on the desired functionality. A flat architecture is more suitable for brainstorming and creative processes, while a vertical hierarchy is generally better suited for rapid decision-making processes (see Figure 1). There are already numerous interesting  studies  on the architecture of such systems and their advantages and disadvantages. The question of whether a flat, horizontal hierarchy, where agents "communicate" on equal footing, or a vertical hierarchy with clearly defined levels is better cannot be answered universally. Organizational developers are likely to understand the concept of a Multi-Agent architecture more quickly and find functional solutions than other experts. Essentially, it is about replicating an organizational structure, down to the level of individual teams. How Expertise is Organized in MAS After choosing the architecture, the next question is how to compose the team to solve tasks in a specific context and achieve defined goals. A proven approach would be to staff the team with different agents, each with the appropriate expertise, focusing on the content in the selection process. In prompt engineering for AIs, this is done, among other things, by assigning roles: "Be an expert in XY and help me solve task Z!" At this point, specialized knowledge databases, known as RAGs (Retrieval-Augmented Generation), also come into play. These extend the expertise of the agents and make the results more reliable.  "A language model like GPT-4, by definition, can only take on and process one role at a time" I will go into more detail about RAGs in another article. These content-functional role assignments work well in Multi-Agent Systems. However, in Single-Agent Systems, this approach has significant limitations. A language model like GPT-4, by definition, can only take on and process one role at a time. Imagine you have a person who is supposed to be the cook, waiter, and cashier in a restaurant at the same time. This person constantly has to switch between tasks, making it easy to make mistakes or lose track. In a Multi-Agent System, however, you have a specialized person for each task: a cook, a waiter, and a cashier. Each can focus on their task, and the restaurant runs much more smoothly. Back to our Multi-Agent Team. Suppose we have successfully staffed it with the right roles and are ready to go. We eagerly press the Enter key and soon find that, despite clearly defined hierarchy and concentrated expertise (role assignments, knowledge databases, tools, etc.), our agents produce hardly any usable results. They either fall into exchanging pleasantries (most models, unfortunately, have been preconditioned by engineers to be nice and helpful) or get stuck in endless iterations without arriving at a useful outcome. What’s going wrong? The dysfunctionality of the team does not lie in the expertise of the team members (role/content) To better trace the cause, think briefly of a team of brilliant experts. This previously high-performing team is integrated into a new line management with a new boss after a restructuring. Shortly thereafter, management finds that the unit has become completely dysfunctional. The new line management and/or the boss are quickly blamed for this failure. The dysfunctionality of the team does not lie in the expertise of the team members (content) but rather in the organizational architecture and the way (form) in which they interact and communicate in the new configuration. But why is this failing, and how can we frame this analysis without unhelpful generalizations like "poor leadership style"? Form-Communication in MAS: The Key to Success This brings us to the topic of "form" – specifically the so-called form of communication, as described in the work of the Peyns on systemic real constructivism. I ask for a bit of patience as I briefly step away from the field of AI to introduce you to the basic principles of communication and form in the shortest possible time. I promise you that the principles discussed can then be directly applied to Multi-Agent Systems. Content vs. Form Unlike focusing on content, such as the expertise of individual agents/employees, the concept of communication form deals with how communication within a system is organized and continuously refers back to itself – or, more precisely, builds on previous communication. The result is a holistic overview of a communication system, the patterns that form within it, and what characteristics and functions these patterns indicate. Figuratively speaking, this systemic bird's-eye view is akin to a fast-forwarded weather animation. You suddenly recognize recurring patterns and seasonal weather phenomena.  Unlike the view of the current weather map, which "only" shows you the current system state, you gain significantly more information from an animation. You understand how the weather system "organizes" itself and how this self-referential organization forms specific patterns. This broad bird's-eye perspective can also be applied to communication systems with great insight. Kadok Plans the Future – A "What If" Game So, imagine briefly ascending with me to a geostationary position 36,000 kilometers high to view a communication system from the perspective of a weather satellite. Below us, we see the fictional company Kadok and the Strategic Foresight department. This department's mission is to derive various future strategies from available signals and identifiable market trends. The goal is to develop successful strategies in a timely manner during a period of significant technological upheaval. The interdisciplinary team consists of five obedient experts and the team leader, Elisabeth, who is equally loved and feared for her clear and assertive leadership style. In short, for simplicity, we are dealing here with a unit that issues commands – represented by the algebraic notation {!,M,V} – and a unit that executes them, {V,M,!}. By the way, the curly brackets, e.g., {V,M,!}, represent the algebraic notation of communication forms according to Ralf and Gitta Peyn. The systemic real constructivism in the Peynian tradition allows me to emulate this communication system, consisting of the forms {!,M,V}{V,M,!}, as an animated weather map in a "What If" game. This is based on a von Neumann cellular automaton (see Glossary) and a total of 6 basic communication forms. These are based on a multi-valued, universal logic of cybernetic knowledge. For now, it suffices to know that this concept stands on the shoulders of scientific giants like von Neumann, Gödel, Luhmann, Brown, Wolfram, Turing, etc. The emulation (Figure 2) of the communication system shows us the following pattern: The visualization of this communication system shows a strong monotony. Nothing is questioned here; instead, work is carried out strictly according to clear instructions. Elisabeth says what needs to be done, and the team understands and executes her instructions. The team expects clear directions from Elisabeth so that they can continue working. In terms of speed, this system is functional. However, this "straight-line" speed may come at the expense of differentiated results. For the goal of strategy development, this communication system as a whole is dysfunctional. Let's try to expand the configuration of the system and introduce more opportunities for discourse. We add an additional communication form, {M,V,!}, in the shape of a critic, let's call him Paul. Paul repeatedly says "Yes, but!" and introduces disruptions into the monotony (see Figure 3). Overall, the system has become somewhat more functional. At least there is now discussion, even if little new insight is generated in the process. We take one final attempt and add another communication form, {!,V,M}, let's call her Sarah. A characteristic of this form is that she communicates a lot and unfiltered. Figure 4 shows that we were able to transform our monotonous communication and decision-making system into one where silo creativity is the predominant system state. Clear "guidelines" can be seen within which the team discusses solutions and develops new approaches. The communication and decision-making architecture of the Strategic Foresight department is now, by the set goal, finally functional. The complete algebraic "formula" for this system is: {!,M,V}{V,M,!}{M,V,!}{!,V,M}. Even if the calculation of system states still seems complicated to you, you may already recognize the immense value of this method. On the drawing board, I can design the ideal architecture of a communication and decision-making system and emulate whether it is functional for my purposes. This applies to both real and virtual teams, such as the Strategic Foresight department or an AI-based Multi-Agent System (MAS).  For an MAS, I simply create virtual agents with the appropriate communication forms, equip them with a mission (prompt) and corresponding knowledge (RAG), and it can start. The MAS becomes an RMAS, a Real Constructivist Multi-Agent System. If you design communication and decision-making systems professionally, whether in organizational development or in the field of AI, the outlined method represents a quantum leap in terms of precision, quality, and cost-efficiency. From Unstable Single-Agents to Powerful RMAS: A Practical Example Let's move into practice.  In Figure 4, I have outlined the architecture of an RMAS for a service provider in the circular economy sector. The goal of this RMAS is to support SMEs in analyzing their linear business models and, using AI and knowledge databases, develop tailored solutions for circular models. The RMAS is not intended to replace human experts but to serve as a low-threshold 24/7 touchpoint to answer initial inquiries and generate qualified leads for consultation with human experts. The RMAS architecture presented in the figure includes, among others, the following agents, precisely organized and orchestrated through the six aforementioned communication forms: Dialogue Agent Analysis Agent Sentiment Agent Business Modelling Agent Target Agent Planning Agent Lead Agent Research Agents Tool Agents etc. The agents are organized into subgroups with different topologies. The communicative interaction of the subgroups, as well as the entire system, can be emulated and tested – as previously demonstrated (see Figure 6).  This is a decisive advantage compared to previous methods and the often hours-long tweaking of increasingly unstable prompts. Whether this RMAS develops new circular economy models or cake recipes with the user doesn’t matter. What’s important is that, as an architect, I can assemble, test, and deploy a functional system with minimal development costs using real constructivist forms – regardless of the content.Initial trials with customers show extremely promising results. In the case of the RMAS in the circular economy sector, it provides a functional brainstorming environment for SMEs, represented by the recurring green triangles. However, more research and testing are needed.  RMAS may also enable us to regain some autonomy from the major AI developers ... We are just at the beginning of understanding how communication systems can be functionally organized.I am very curious to see where the development of large language models will go in the coming months. It seems clear that we will hardly be able to avoid MAS or RMAS – if only for reasons of cost and efficiency. RMAS may also enable us to regain some autonomy from the major AI developers. With RMAS, even smaller open-source LLMs can be expanded into powerful and efficient systems. More information and benchmarks on this topic can be found in this exciting article by Andrew Ng (2024),  Agentic Design Patterns . AI Agents Solve Complex Business Problems and Help Scale Processes Autonomous 24/7 Touchpoints:  RMAS can be continuously used for customer and employee interactions without human intervention. Expert and Copilot Systems:  Support in handling complex tasks through specialized agents that offer expertise and recommendations. Dialogue Bots:  Use of RMAS for generating qualified leads and improving customer communication. Process Automation:  Automation of recurring and complex processes that require manual interventions. Creative and Innovation Processes:  Promotion of creative ideas and innovations through structured brainstorming and thinking processes. Risk Management:  Proactive identification and minimization of risks through continuous monitoring and analysis. Educational and Training Systems:  Creation of adaptive learning and training programs tailored to the needs of learners. Product Development:  Support in developing new products through coordinated collaboration and efficient resource utilization. Research and Development:  Acceleration of research processes through structured data analysis and knowledge management. With RMAS, even smaller open-source LLMs can be expanded into powerful and efficient systems Conclusion: The Future of AI Systems with Real Advantages Lies in RMAS Nature impressively shows us how simple systems become more intelligent and solve more demanding tasks when combined. The foundational research of the Peyns is, for me, comparable to the "Philosopher's Stone," a mythical substance that ancient alchemists claimed could turn lead into gold in the minds of the gullible. Unlike alchemy, however, systemic real constructivism provides a modern, empirical foundation to create powerful RMAS for a variety of tasks and challenges – without sleight of hand, esoteric prompts, and ever-larger models with ever-greater energy requirements.Are you ready to elevate your company or institution to the next level of AI development? Discover the possibilities that RMAS offer and how they can optimize, scale, and enhance your innovation capabilities. Contact me for a free consultation and learn how AI Agents can solve complex business problems. Patrick Castellani, 2024 Further Reading and Publications Masterman, Sawtell, Besen, Chao (2024),  The Landscape of Emerging AI Agent Architectures for Reasoning, Planning, and Tool Calling: A Survey   Andrew Ng (2024),  Agentic Design Patterns Penrose (2016),  The Emperor's New Mind , Oxford Landmark Science Hameroff, Penrose (2013),  Consciousness in the Universe – A review of the ‘Orch OR’ theory Ralf Peyn (2024),  FORMcalculus , Formwelt Media  Ralf Peyn (2017),  uFORM iFORM , Ralf Peyn, Carl Auer Verlag Gitta & Ralf Peyn (2024),  Realkonstruktivismus , Formwelt Media, book excerpt:  https://formwelt.io/media/ Michael Levin (2019),  The Computational Boundary of a “Self”: Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition ,  Harvard University Glossary Artificial Intelligence (AI):  A field of computer science focused on developing systems and machines that mimic human intelligence. AI encompasses technologies such as machine learning, neural networks, and algorithms capable of performing tasks like speech recognition, image recognition, and decision-making. Large Language Model (LLM):  An AI model trained on large amounts of text to understand and generate human language. Examples of LLMs are GPT-3 and GPT-4. These models use extensive data and complex algorithms to provide contextually relevant and meaningful responses. Single-Agent:  A system or application where only a single agent (program or robot) operates. The single agent functions independently and does not interact with other agents. Such systems are easier to implement but have limited capabilities compared to multi-agent systems. Multi-Agent:  A system where multiple agents interact and cooperate to solve complex tasks. Each agent has specialized skills and roles. Multi-agent systems offer higher flexibility, scalability, and problem-solving capacity through the collaboration of agents. One-Shot:  In the context of prompting, "one-shot" refers to a technique where an AI model is given only a single example or prompt to complete a task. This contrasts with "few-shot" or "zero-shot" techniques, where either multiple examples or no specific examples are provided. Prompting:  The technique of providing an AI model with specific inputs (prompts) to generate certain outputs. Prompts can be questions, instructions, or hints that guide the model's behavior. Prompting is often used to improve the performance and accuracy of LLMs. Integrated Scale-Free Cognition:  A concept in cognitive science describing how biological systems exhibit intelligent and goal-directed behaviors through the cooperation of many small, specialized units. "Scale-free" means these systems show similar patterns and principles of self-organization and problem-solving at various levels of organization, from cells to entire organisms. Integrated scale-free cognition emphasizes that a system's intelligence arises not from a single level but through the interactions and networks of many components working together to tackle complex tasks. Systemic Real Constructivism:  A theoretical approach that views reality as the result of constructive processes within systems. This theory emphasizes that knowledge and reality are generated and maintained through a system's interactions and structures. In the context of AI, this refers to how systems construct and apply knowledge. Cellular Automata:  Mathematical models for complex systems consisting of a grid of cells, each with a state that changes according to specified rules. Cellular automata can be used to simulate natural phenomena such as growth, pattern formation, and self-organization. Cybernetics:  The science of control and regulation in systems, whether in machines, biological organisms, or social structures. Cybernetics studies how systems process information, make decisions, and adapt to changing environments. It forms the foundation for many fields in computer science and systems theory. Emergence:  The phenomenon where complex patterns or properties arise in a system from the interactions of its simple components. Emergence occurs when the whole system exhibits capabilities or behaviors that cannot be directly derived from the properties of individual components. Consciousness:  A state of the human mind involving the experience and perception of thoughts, feelings, and environments. In AI, consciousness is a controversial and as yet unattained goal, as it goes beyond mere data processing to require self-awareness and subjective experience.

In working with purpose-driven organizations, I’ve seen how aligning strategy  with a well-defined purpose  can make a profound difference—not only in terms of business success but in creating meaningful, lasting impact. While it sounds straightforward, the practicalities of merging strategic goals with a higher purpose often require careful navigation. This is where Changemakers —those who champion the integration of purpose into everyday actions—play a key role, ensuring that purpose is not just an aspiration but a tangible part of business operations. The Quiet Drivers of Purpose-Led Innovation Changemakers don’t always take the spotlight, but they are instrumental in bridging the gap between purpose  and strategy . They ensure that a company’s mission is reflected not just in its public-facing values but in its internal processes and day-to-day operations. Companies like Patagonia  and Mud Jeans  exemplify how Changemakers help embed sustainability deeply into their business models, ensuring that initiatives are aligned with both financial performance and broader social goals. For example, Mud Jeans  has embraced a circular economy by introducing a leasing model for jeans, allowing customers to return worn jeans for recycling. This is a clear demonstration of how purpose can guide operational decisions, creating a balance between profit and sustainability. Such models work best when companies track both financial outcomes  and social impact  using dual KPIs —a practice that ensures purpose remains central to decision-making​ ( ClimateSort ) ​( Sustainable Jungle ). Alignment: Balancing Long-Term Strategy and Purpose with Operational Realities Aligning purpose with strategy requires more than just a strong vision. I’ve observed that organizations sometimes struggle to connect their broader mission with everyday execution. This misalignment can often lead to demotivation and a dilution of purpose. In my experience, creating effective feedback loops  is essential for maintaining alignment between leadership’s goals and the realities on the ground. Consistent communication  plays a critical role in this process. When employees understand how their work contributes to the company’s mission, engagement improves and the gap between strategy and operations narrows. By establishing a clear connection between purpose  and the tactical execution of day-to-day tasks, companies can ensure that their mission isn’t lost in the operational grind ​( Harvard Business ) ​( MyCystalGroup ). Overcoming Common Obstacles: From Resources to Metrics One of the most common challenges I’ve encountered is resource allocation . Teams are often passionate about their purpose-driven projects, but without sufficient support, these initiatives can falter. Ensuring fair and transparent resource allocation  is crucial for maintaining momentum. This involves directing resources in a way that supports the company’s long-term mission while also meeting short-term financial targets​ ( Harvard Business ). In addition, measuring success  in a purpose-driven organization requires more than financial metrics. Implementing dual KPIs —tracking both profit and social or environmental impact—has proven to be an effective approach for many of the organizations I’ve worked with. These metrics offer a balanced view of performance, ensuring that purpose remains integral to the company’s long-term strategy​ ( The CEO Magazine ) ( MyCystalGroup ). Case Studies: Learning from Leaders in Purpose and Strategy Several companies provide excellent examples of how to successfully align purpose with strategy. Mud Jeans  has set a standard for circular fashion by enabling customers to lease and recycle their jeans, effectively closing the loop on waste ​( ClimateSort ). Winnow , another example, has revolutionized the food service industry by using smart technology to reduce food waste in commercial kitchens, demonstrating how purpose-led innovation can generate both financial and environmental benefits​ ( World Economic Forum ). Similarly, Close the Loop , an Australian company, turns soft plastics and printer cartridges into materials for road construction, showcasing how a strong purpose can drive innovative business solutions that address significant environmental challenges​ ( World Economic Forum ). Takeaways for Leaders: Communicate Purpose Regularly : To keep purpose central to your strategy, it’s essential to ensure that leadership consistently reinforces the company’s mission at all levels​ ( Harvard Business ). Establish Dual KPIs : Measure both financial performance and social or environmental impact to maintain balance between profit and purpose​ ( The CEO Magazine ). Leverage Changemakers : Empower individuals within your organization to act as bridges between strategy and operations, ensuring that purpose is reflected in daily activities​ ( McKinsey & Company ). Optimize Resource Allocation : Fairly distribute resources to ensure that all teams have the necessary support to drive purpose-led initiatives​ ( Harvard Business ). Create Feedback Loops : Regularly gather employee feedback to ensure that purpose remains relevant and actionable across all departments​ ( MyCystalGroup ). Conclusion: A Path Forward for Purpose-Driven Organizations As businesses continue to evolve, the alignment of strategy  and purpose  will remain a critical factor in long-term success. From what I’ve observed, the companies that manage this balance most effectively are those that embrace Changemakers —those who quietly ensure that purpose is woven into every aspect of the organization. Going forward, it will be these businesses that not only thrive in competitive markets but also leave a lasting, positive impact on society. By keeping purpose central and aligning it with everyday operations, organizations can achieve sustainable growth without losing sight of their core mission. Patrick Castellani Glossary: Changemaker : A person within an organization who ensures that purpose aligns with strategy and operations​ ( HRForecast ). Strategic Alignment : The process of ensuring that an organization’s strategy supports its long-term purpose​ ( McKinsey & Company ). Circular Economy : A system focused on reducing waste by reusing and recycling materials​ ( Sustainable Jungle ). Dual KPIs : Metrics that measure both financial outcomes and social or environmental impact​ ( The CEO Magazine ). Resource Allocation : The distribution of resources (e.g., time, funding, and personnel) to support strategic initiatives​ ( Default ). Sources and References: McKinsey & Company : Connecting Strategy, Goals, and Meaningful Purpose ​ ( McKinsey & Company ). McChrystal Group : Everything You Need to Know About Strategy Alignment ​ HRForecast : Creating Purpose-Oriented Organizations ​ ( HRForecast ). ClimateSort : 12 Leading Circular Economy Companies & Start-Ups ​ ( ClimateSort ). Sustainable Jungle : 9 Circular Economy Companies Keeping The Planet Well-Rounded ​( Sustainable Jungle ). The CEO Magazine : How to Create a Purpose-Driven Organization ​ ( The CEO Magazine ).

Definition: Dual KPIs (Key Performance Indicators) are a strategic measurement system that pairs two distinct metrics to provide a more complete picture of performance. While traditional KPIs focus on a single outcome—like revenue, customer growth, or product quality—Dual KPIs track two related yet separate goals, such as balancing financial outcomes with social or environmental impact. This is especially relevant for purpose-driven and circular economy models, where both profitability and sustainability are critical to long-term success. Mental Shortcut: Imagine steering a ship: traditional KPIs are like focusing solely on speed, but Dual KPIs are like watching both speed and direction. Going fast (financial success) is pointless if you’re veering off course (ignoring sustainability or social impact). Application: Dual KPIs are increasingly used by organizations striving to balance financial goals with long-term sustainability. For example, a company might monitor profit margin  alongside employee retention rates , ensuring the workforce is not sacrificed for higher profits. Another example is tracking net sales  while reducing the company’s carbon footprint , ensuring growth doesn’t come at the environment’s expense. Examples: Patagonia:  Patagonia tracks financial performance alongside its environmental and social impact. The company focuses on metrics such as reducing its carbon footprint, sustainable sourcing of materials, and fair labor practices. A real example of this dual focus can be seen in their decision to donate 1% of sales to environmental causes through their 1% for the Planet  initiative. Their 2018 Patagonia Case Study  shows how they have maintained profitability while championing environmental sustainability. Patagonia Case Study . Unilever:  Unilever tracks both financial and social/environmental KPIs through its Sustainable Living Plan . By 2020, 67% of Unilever’s products reduced environmental impact while maintaining strong financial growth. For example, their "Lifebuoy" soap campaign helped improve hygiene in developing countries while increasing sales. The company’s 2020 Sustainable Living Report  demonstrates how it has improved revenue and minimized environmental impact. Unilever’s Sustainable Living Plan . Ben & Jerry’s:  This socially responsible ice cream company has consistently balanced profitability  with social justice  and environmental KPIs . Their “Caring Dairy” initiative supports sustainable farming practices while maintaining product quality and profitability. Ben & Jerry’s 2020 Social and Environmental Assessment Report  outlines how they track revenue growth alongside key metrics like reduced energy usage and community support. Ben & Jerry’s SEAR. Benefits: Balanced decision-making:  Helps leaders make informed choices by weighing both short-term wins and long-term outcomes. Alignment with purpose:  Drives company performance while staying true to the organization's mission and values. Stakeholder engagement:  Shows investors, consumers, and employees that the company cares about more than just financial success. Improved resilience:  Mitigates risk by diversifying focus, avoiding over-reliance on one-dimensional success metrics. Challenges: Complexity in balancing:  Combining two different KPIs—like sustainability metrics with financial results—can create conflicting priorities. Data integration hurdles:  Gathering real-time data for two distinct KPIs can require advanced systems, which not all organizations have. Cultural resistance:  Teams may resist the dual focus, particularly if they are accustomed to prioritizing financial targets alone. Short-termism pressure:  There is often external pressure, especially from investors or board members, to prioritize short-term gains over long-term objectives. This tension can lead to sacrificing sustainable or social goals in favor of immediate financial results. For instance, Unilever faced a challenge when its shift to sustainable packaging led to higher initial costs. However, by balancing sustainability with revenue targets, the company found long-term profitability through enhanced brand loyalty and operational efficiency. Unilever Packaging Initiative. What Not to Do: An example of failure in balancing Dual KPIs can be seen in the tech industry, where companies that prioritize user growth (financial KPI) without considering data privacy (non-financial KPI) can face significant backlash. Facebook  experienced this with the Cambridge Analytica scandal, where prioritizing growth and advertising revenue over ethical data use led to a significant loss of public trust and financial penalties. How to Start with Dual KPIs: Define your values:  Identify two dimensions that matter most to your organization (e.g., revenue growth and community engagement). Align stakeholders:  Ensure leadership and teams understand the importance of tracking both KPIs and how they will benefit the organization. Coordinate across departments:  Ensure that different departments (e.g., finance, sustainability, HR) are aligned with the goals, so all efforts push toward achieving both KPIs simultaneously. Invest in tools:  Use platforms that integrate financial and non-financial metrics (e.g., sustainability tracking software). Regular reviews:  Hold quarterly meetings to assess performance across both KPIs and adjust strategies accordingly. Frameworks & Tools: Balanced Scorecard:  This well-established framework helps organizations pair financial outcomes with non-financial drivers such as innovation, customer satisfaction, and sustainability. Balanced Scorecard Review . B Impact Assessment:  This tool measures a company’s impact on its workers, community, environment, and customers, helping businesses track their progress toward holistic goals. Learn more at B Impact Assessment . Global Reporting Initiative (GRI):  A standard used by organizations to measure and report their sustainability impacts alongside financial performance. See more at GRI Standards . Ecovadis:  Provides sustainability ratings and performance reviews for global supply chains, helping companies align their sustainability and financial goals. More details at Ecovadis . Related Terms: Balanced scorecard, Triple bottom line, Impact measurement, Sustainability metrics, ESG reporting, Circular economy KPIs, Stakeholder capitalism, Long-term value creation Sources and References: Kaplan, Robert S., and David P. Norton. The Balanced Scorecard: Translating Strategy into Action.  Harvard Business Review Press, 1996. Balanced Scorecard Reference Patagonia's Environmental Responsibility: Patagonia Case Study Global Reporting Initiative (GRI) Standards: GRI Standards Unilever’s Sustainable Living Plan: Unilever Case Study Ben & Jerry’s Social and Environmental Assessment Report: Ben & Jerry's SEAR

Definition: The Triple Bottom Line (TBL)  is a sustainability framework that encourages businesses to go beyond traditional financial metrics (the "bottom line") and measure their success in three areas: People , Planet , and Profit . Introduced by John Elkington in the mid-1990s, the TBL emphasizes that a company's responsibility extends beyond shareholders to include social and environmental stakeholders. In this model, economic success (profit) is integrated with social well-being (people) and environmental health (planet). The goal is to create a balanced approach to growth that considers long-term impact over short-term gains. Source:  Elkington, John. Cannibals with Forks: The Triple Bottom Line of 21st Century Business . Summary on Triple Bottom Line Mental Shortcut: Think of the Triple Bottom Line as a three-legged stool: if one leg (Profit, People, or Planet) is missing or unstable, the whole stool collapses. A business might be financially successful, but if it’s harming the environment or society, the foundation of that success won’t hold. Application: The Triple Bottom Line is increasingly used by organizations focused on sustainable development  and corporate social responsibility (CSR) . It pushes companies to adopt practices that ensure fair labor , reduce carbon footprints , and give back to communities  while maintaining profitability. Examples: Seventh Generation:  This eco-friendly cleaning and household products company is dedicated to the TBL philosophy. They focus on sustainable production, ensuring products are safe for both people and the planet. Seventh Generation commits to using plant-based ingredients, recycled packaging, and ethical sourcing, while ensuring fair wages for workers. Their 2020 Sustainability Report  details their efforts to minimize environmental impact and increase social equity. Seventh Generation Sustainability Report. Patagonia:  A TBL pioneer, Patagonia evaluates its operations on financial success, environmental responsibility, and social equity. Their ongoing efforts to use recycled materials and ensure fair wages exemplify how TBL drives decision-making. Patagonia’s commitment to donating 1% of sales to environmental causes through its 1% for the Planet  initiative demonstrates the TBL in action. Patagonia’s Environmental Initiatives . Unilever:  Unilever’s Sustainable Living Plan  uses TBL to measure success across environmental impact (Planet), social well-being (People), and financial growth (Profit). The plan resulted in 67% of Unilever’s products reducing their environmental footprint while delivering solid financial results. Unilever’s Sustainable Living Plan . Benefits: Enhanced reputation:  Boosts brand credibility by aligning with stakeholder values on sustainability and ethics. Risk management:  Minimizes risks related to environmental damage or poor labor practices, which can lead to legal or reputational issues. For instance, Ben & Jerry’s  has reduced risk through transparent reporting on social and environmental issues, resulting in high consumer trust. Ben & Jerry’s SEAR Report. Long-term profitability:  Investing in people and the planet strengthens consumer loyalty, which can lead to sustainable growth. Employee engagement:  Purpose-driven organizations attract and retain talent who are motivated by more than just financial incentives. Market differentiation:  Companies with a strong TBL strategy stand out in competitive markets as ethical and sustainable leaders. Patagonia’s brand image  is closely tied to its environmental advocacy, helping it differentiate in the outdoor apparel market. Patagonia Activism. Challenges: Balancing priorities:  Companies may struggle to balance the financial with social and environmental metrics, especially when immediate profit pressures conflict with longer-term sustainability goals. Complex measurement:  Quantifying social and environmental impacts is not always straightforward and can require sophisticated tools and frameworks. GRI Standards  offer guidance on how to report environmental, social, and governance metrics comprehensively. Global Reporting Initiative. Higher initial costs:  Investments in sustainable practices, such as sourcing eco-friendly materials, can lead to higher upfront expenses, with delayed financial returns. For example, Unilever  faced higher operational costs when transitioning to sustainable packaging, but in the long run, it led to cost savings and brand loyalty from environmentally conscious consumers. Unilever’s Plastic Packaging Initiative. What Not to Do: A notable example of failure in implementing TBL properly comes from BP , where the company’s overemphasis on profit (one leg of the stool) and underinvestment in environmental safety (the "Planet" leg) resulted in the Deepwater Horizon oil spill . This disaster not only harmed the environment but also caused immense reputational and financial damage, demonstrating the risks of an unbalanced approach. BP Deepwater Horizon Disaster . How to Start with the Triple Bottom Line: Assess your impact:  Identify your company’s current social, environmental, and economic impact. Small steps—such as reducing energy consumption or switching to ethical suppliers—can make a big difference over time. Seventh Generation , for example, started with ethical sourcing and gradually scaled up its sustainability practices. Seventh Generation Sustainability Journey. Set clear goals:  Develop measurable KPIs across the three pillars of People, Planet, and Profit. For instance, Patagonia  started by setting small goals on product sustainability before scaling their efforts to achieve major environmental impact. Patagonia Sustainability Goals. Engage stakeholders:  Align your team, shareholders, and community with the TBL mission. Encourage buy-in by demonstrating how each pillar benefits both the organization and its stakeholders. For example, Unilever’s stakeholder engagement  helped gain global support for its sustainable initiatives. Unilever Stakeholder Engagement. Report regularly:  Adopt transparent reporting practices using frameworks like the Global Reporting Initiative (GRI) . Regular reports ensure accountability and help track progress. GRI Sustainability Reporting. Invest in sustainable innovation:  Allocate resources to new technologies or processes that reduce environmental harm or enhance social good. Many companies start with small, pilot projects before expanding their initiatives. For example, Patagonia’s pilot program  with recycled fabrics helped test viability before scaling to broader production. Patagonia Recycled Materials. Frameworks & Tools: B Corporation Certification:  Measures the social and environmental performance of companies and ensures they meet high standards of accountability and transparency. Learn more at B Corporation. Global Reporting Initiative (GRI):  Helps businesses track their economic, environmental, and social impacts in a comprehensive report. See more at GRI Standards . Sustainability Accounting Standards Board (SASB):  Provides guidelines for integrating sustainability factors into financial reporting. Explore at SASB Standards . Carbon Disclosure Project (CDP):  A reporting system used to measure environmental impact, helping companies track their carbon footprint and climate-related risks. CDP Overview . Related Terms: Sustainability reporting, Corporate social responsibility (CSR), ESG (Environmental, Social, and Governance), Stakeholder capitalism, Circular economy, Social impact, Environmental metrics, Sustainable growth, Long-term value creation, Sustainable business strategy, Balancing profit and purpose Sources and References: Elkington, John. Cannibals with Forks: The Triple Bottom Line of 21st Century Business . Summary on Triple Bottom Line Global Reporting Initiative (GRI):   GRI Standards . Patagonia’s Environmental Responsibility:   Patagonia Case Study . Unilever’s Sustainable Living Plan:   Unilever Case Study . Seventh Generation’s Sustainability Report:   Seventh Generation Report.

Definition: Long-term value creation refers to a business strategy focused on building sustainable growth and profitability over time, rather than prioritizing short-term financial gains. It emphasizes the need for companies to invest in innovation, employee development, customer relationships, and sustainable practices that lead to ongoing benefits for shareholders, employees, and society. This approach integrates financial performance with non-financial factors such as social responsibility, environmental impact, and governance (often referred to as ESG metrics). Companies that pursue long-term value creation aim to remain competitive, resilient, and purpose-driven in an ever-evolving market landscape. Mental Shortcut: Think of long-term value creation as planting a tree: while short-term actions (quick profits) might resemble picking low-hanging fruit, long-term value creation is like investing in the health and growth of the tree, ensuring it bears fruit season after season. Application: Many companies that prioritize long-term value creation do so by embedding sustainability , employee well-being , and innovation into their core operations. Rather than focusing solely on quarterly profits, they aim to generate lasting benefits for all stakeholders. Examples: Interface: As a leader in sustainable manufacturing, Interface, a modular carpet company, focuses on long-term value creation by committing to environmental sustainability and circular economy principles. Through its Mission Zero initiative, Interface worked to eliminate negative environmental impact by 2020. The company continues to invest in low-impact materials, renewable energy, and recycling practices, aiming for carbon negativity by 2040. Learn more about Interface’s Mission Zero and its transition to Climate Take Back  initiatives here . Schneider Electric:  This global energy management company follows a strategy of long-term value creation  by focusing on digital innovation and sustainability. Through its energy management and automation solutions, Schneider helps customers and industries transition to more efficient and sustainable operations. Explore Schneider Electric's Sustainability Report . Novo Nordisk:  The pharmaceutical company aligns its business goals with societal benefits by developing treatments for chronic diseases while ensuring access to affordable medicine. By integrating sustainability into its core, it seeks to create long-term value both for shareholders and patients. Read Novo Nordisk's Annual Report . Benefits: Sustainable growth:  Creates resilience by focusing on long-term strategies rather than short-term profits. Stakeholder trust:  Builds stronger relationships with investors, employees, and customers by demonstrating a commitment to long-term impact and stability. Risk mitigation:  Reduces risk by diversifying focus beyond financial metrics and incorporating social, environmental, and governance aspects. Innovation driver:  Encourages investment in research and development to adapt to future market needs and challenges. Employee retention:  Attracts talent who are aligned with the organization’s purpose and long-term vision, leading to higher employee satisfaction and retention. Challenges: Balancing short- and long-term goals:  Companies often face pressure from shareholders for quick financial returns, which can conflict with strategies aimed at long-term value creation. Cultural shift:  Adopting a long-term mindset may require a significant cultural change within the organization, especially in industries driven by short-term performance metrics. Upfront investment costs:  Long-term value strategies often involve heavy initial investments in areas such as sustainability, innovation, or employee development, with returns manifesting only over time. For instance, Schneider Electric  has made substantial upfront investments in digital technologies and sustainability efforts, which, although costly initially, have strengthened its position in the green energy market. How to Start with Long-term Value Creation: Integrate ESG goals:  Embed environmental, social, and governance (ESG) factors into the business strategy. Commit to innovation:  Invest in long-term research and development to ensure your company adapts to changing market demands. Focus on stakeholder value:  Balance shareholder profits with the needs of employees, customers, and society. Adopt transparent reporting:  Provide regular updates on progress toward long-term goals, using frameworks like the Global Reporting Initiative (GRI) . Develop leadership vision:  Cultivate leaders within the organization who are aligned with long-term value creation goals and can inspire a shift in focus. Frameworks & Tools: Integrated Reporting Framework (IRF):  This framework helps organizations communicate how they create value over the short, medium, and long term through financial and non-financial reporting. Learn more about IRF. Sustainability Accounting Standards Board (SASB):  Provides standards for reporting on sustainability-related risks and opportunities that are material to long-term value. Discover SASB standards. Global Reporting Initiative (GRI):  Supports businesses in tracking and reporting their economic, environmental, and social impacts, which are key to long-term value creation. Explore GRI Standards. Related Terms: Sustainable growth, ESG integration, Stakeholder capitalism, Long-term investment strategy, Value-driven leadership, Corporate responsibility, Sustainable innovation, Resilience strategy Sources and References: Interface’s Sustainability Commitment: Interface Mission Zero Schneider Electric’s Sustainability Report: Schneider Electric Sustainability Report Novo Nordisk Annual Report: Novo Nordisk Annual Report Sustainability Accounting Standards Board (SASB): SASB Standards Global Reporting Initiative (GRI): GRI Standards Integrated Reporting Framework (IRF): IRF Overview

Why Most Corporate Values Initiatives Fail: The Iceberg You’re Not Seeing Why do so many company value initiatives fall flat? Most organizations focus only on what’s visible—the 10% that sits above the surface. But the real power of corporate values lies beneath—the hidden 90% that actually drives behavior, engagement, and culture. Without tapping into that, you’re left with superficial initiatives that fail to gain traction. Last week, I conducted a workshop for a Swiss healthcare company on the topic of values. Our goal was to develop strategies and methods for launching a values initiative across the entire workforce. But here's the thing: values can’t simply be “rolled out” like a new product. You have to go much deeper. Let’s explore why this is, using one of my favorite metaphors: the iceberg. The 90% That Drives Success: Understanding the Invisible Forces of Culture As you probably know, only 10% of an iceberg is visible above the water; the remaining 90% lies hidden beneath the surface. In terms of impact, the visible 10% is only there because of the massive force pushing up from below. My old physics teacher might wince at the oversimplification, but bear with me! In organizations, there’s a visible and an invisible world. Sending a PDF with new values to all employees happens in the visible world. At best, it’s read and filed away. At worst, it’s ignored altogether. The outcome: zero impact. Sound familiar? According to Gallup , only 27% of employees strongly believe in their company’s values. Why? Because most initiatives stay at the surface, focusing only on policies, documents, or top-down communications​. But to truly move people, you need to address the invisible 90%. The Storytelling Edge: Why Words Alone Aren’t Enough To move people in the visible 10%, you first have to move the hidden 90%. But how do you do that? The answer lies in storytelling. Can stories move people? Absolutely. Research by Paul Zak  shows that storytelling boosts oxytocin production, a neurochemical that fosters empathy and trust​ . This means that stories have a unique ability to create emotional connections that facts or figures simply cannot. When companies share their values through personal stories, they do more than just communicate—they forge emotional ties that make those values resonate deeply with employees. And this emotional connection is what drives real cultural change. Neuroscientifically, stories activate multiple areas of the brain, engaging both logic and emotion, which makes them a powerful tool for influencing behavior . Take Patagonia  for example. Their environmental values aren’t just words on a page—they are embedded in every action. When Patagonia closed its stores on Black Friday to protest consumerism, they weren’t just talking about values; they were living them. This action not only resonated with employees but also aligned the brand with customers who shared the same values . Bringing Values to Life: How Stories Shape Organizational Identity In my workshop with the healthcare company, we didn’t focus on distributing a document of values. Instead, we used storytelling to bring the values of humanity  and professionalism  to life. Participants shared personal experiences that illustrated these values in action. One story stood out: an employee described how a simple gesture, like addressing a patient by their name, created a profound emotional impact. Another story detailed how a team of 12 experts gathered around an MRI scan, ready to act immediately based on the results. These stories weren’t abstract—they were tangible experiences that made the values real for everyone involved. This process wasn’t just about collecting anecdotes; it was a catalyst for cultural change. By the end of the day, we didn’t just have strong values stories. We had started a real cultural shift. Employees aligned their personal experiences with the company’s values, creating a shared identity. The results? Employee engagement increased by 15% in the months following the workshop. Leaders began incorporating these stories into team meetings, making values a living part of the daily culture. What started as a storytelling exercise became the foundation of a cultural transformation . The Invisible Levers of Culture: How to Move What Matters Most So, why are stories so effective at shaping culture? The answer lies in the fact that they engage both the conscious and subconscious mind. By activating multiple areas of the brain, stories help coordinate actions, create meaning, and synchronize our perception of the world . In the visible world, distributing a values statement will do little to change behavior. But when employees share and connect with stories that reflect those values, they’re not just receiving information—they're internalizing it. In narrative workshops like the one I conducted, companies can uncover powerful stories from within their own ranks. This not only helps make values concrete but also taps into the hidden 90% that truly drives organizational culture. From Values to Action: Tapping into the Cultural Forces That Drive Real Change If you want to make values more than just words on a page, you need to go beneath the surface. You need to tap into the experiences and emotions of your people. Because it’s in those hidden 90% where the real cultural magic happens. For further reading, I highly recommend the book Corporate Storytelling  by Christine Erlach  and Michael Müller , which dives deep into how narrative methods can transform organizations . References Gallup Workplace Study, Gallup.com . Zak, P. (2014). "Why Your Brain Loves Good Storytelling," Harvard Business Review , hbr.org . Patagonia’s Black Friday Story, The Guardian  (2016), theguardian.com . Employee Engagement and Storytelling Study, MIT Sloan Management Review  (2020), mitsloan.mit.edu . Erlach, C. & Müller, M. (2019). Corporate Storytelling: A Narrative Approach to Organizational Change . Springer.